COSIBAS Platform-Cognitive Services for IoT-Based Scenarios: Application in P2P Networks for Energy Exchange

Area of Science:

• Computer Science
• Artificial Intelligence
• Internet of Things

Background:

• The Internet of Things (IoT) connects numerous devices, generating valuable data for decision-making.
• Data heterogeneity across IoT devices presents significant challenges for integration and knowledge acquisition.
• Existing systems struggle to interoperate with emerging IoT and AI technologies.

Purpose of the Study:

• To address the challenge of data integration and knowledge acquisition in IoT environments.
• To develop a solution combining semantic technologies and artificial intelligence for actionable insights.
• To create an abstraction layer for seamless interoperability between IoT and AI platforms.

Main Methods:

• Utilizing IoT semantic data for knowledge reasoning.
• Integrating next-generation semantic technologies with artificial intelligence components.
• Developing COSIBAS, a cognitive artificial intelligence service platform.
• Building an abstraction layer between IoT and AI technologies.

Main Results:

• Enabling easy interoperability and integration for legacy and emerging technologies.
• Generating business value through faster analytics and improved decision-making.
• COSIBAS provides a low-cost, cross-platform solution supporting scalability.
• Facilitating the modernization of legacy infrastructures with cognitive tools.

Conclusions:

• Combining IoT and cognitive AI services via COSIBAS enhances interoperability across domains.
• The proposed solution effectively addresses the challenge of semantic data integration in IoT.
• COSIBAS supports the evolution of large-scale heterogeneous systems and asset reuse.